{"title":"Single-cell Micro-C profiles 3D genome structures at high resolution and characterizes multi-enhancer hubs","authors":"Honggui Wu, Jiankun Zhang, Longzhi Tan, Xiaoliang Sunney Xie","doi":"10.1038/s41588-025-02247-6","DOIUrl":null,"url":null,"abstract":"In animal genomes, regulatory DNA elements called enhancers govern precise spatiotemporal gene expression patterns in specific cell types. However, the spatial organization of enhancers within the nucleus to regulate target genes remains poorly understood. Here we report single-cell Micro-C (scMicro-C), a micrococcal nuclease-based three-dimensional (3D) genome mapping technique with an improved spatial resolution of 5 kb, and identified a specialized 3D enhancer structure termed ‘promoter–enhancer stripes (PESs)’, connecting a gene’s promoter to multiple enhancers. PES are formed by cohesin-mediated loop extrusion, which potentially brings multiple enhancers to the promoter. Further, we observed the prevalence of multi-enhancer hubs on genes with PES within single-cell 3D genome structures, wherein multiple enhancers form a spatial cluster in association with the gene promoter. Through its improved resolution, scMicro-C elucidates how enhancers are spatially coordinated to control genes. scMicro-C is a new method that provides high-resolution maps of the 3D genome. scMicro-C identifies structures called ‘promoter stripes’, which link a gene promoter to multiple downstream enhancers.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"57 7","pages":"1777-1786"},"PeriodicalIF":29.0000,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-025-02247-6.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature genetics","FirstCategoryId":"99","ListUrlMain":"https://www.nature.com/articles/s41588-025-02247-6","RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
引用次数: 0
Abstract
In animal genomes, regulatory DNA elements called enhancers govern precise spatiotemporal gene expression patterns in specific cell types. However, the spatial organization of enhancers within the nucleus to regulate target genes remains poorly understood. Here we report single-cell Micro-C (scMicro-C), a micrococcal nuclease-based three-dimensional (3D) genome mapping technique with an improved spatial resolution of 5 kb, and identified a specialized 3D enhancer structure termed ‘promoter–enhancer stripes (PESs)’, connecting a gene’s promoter to multiple enhancers. PES are formed by cohesin-mediated loop extrusion, which potentially brings multiple enhancers to the promoter. Further, we observed the prevalence of multi-enhancer hubs on genes with PES within single-cell 3D genome structures, wherein multiple enhancers form a spatial cluster in association with the gene promoter. Through its improved resolution, scMicro-C elucidates how enhancers are spatially coordinated to control genes. scMicro-C is a new method that provides high-resolution maps of the 3D genome. scMicro-C identifies structures called ‘promoter stripes’, which link a gene promoter to multiple downstream enhancers.
期刊介绍:
Nature Genetics publishes the very highest quality research in genetics. It encompasses genetic and functional genomic studies on human and plant traits and on other model organisms. Current emphasis is on the genetic basis for common and complex diseases and on the functional mechanism, architecture and evolution of gene networks, studied by experimental perturbation.
Integrative genetic topics comprise, but are not limited to:
-Genes in the pathology of human disease
-Molecular analysis of simple and complex genetic traits
-Cancer genetics
-Agricultural genomics
-Developmental genetics
-Regulatory variation in gene expression
-Strategies and technologies for extracting function from genomic data
-Pharmacological genomics
-Genome evolution